Swarooph Nirmal Seshadri (@sseshadr)
github

sseshadr

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  • Stars
    star
    42
  • Global Rank 385,755 (Top 14 %)
  • Followers 23
  • Registered almost 11 years ago
  • Most used languages
    MATLAB
         71.4 %
    C++
         14.3 %
    Jupyter Notebook
         14.3 %

Top repositories

1

auvsi-cv-pointCloud

Learn how to read, load and visualize point clouds using MATLAB and pre-process the data by down sampling and de-noising. You will also learn how to apply affine transforms like translation and rotation. Finally, you will learn how to fit point clouds to geometric shapes and how to extract a region of interest from images using point clouds.
MATLAB
10
star
2

auvsi-cv-stereoVision

Learn how to import and display stereo vision images. Also understand how to calibrate stereo cameras, rectify images to align them horizontally, generate disparity maps and create point clouds with scene reconstruction.
MATLAB
5
star
3

auvsi-cv-lineDetection

Learn how to detect lines using MATLAB. The concept of a Hough Transform is demonstrated to show how to use them to extract line segments. Tips on some preprocessing techniques are also provided to improve line detection results. An example of lane detection is used to explain these concepts.
MATLAB
5
star
4

auvsi-cv-objectTracking

Learn how to track an object across video frames. Object tracking using histogram based tracking, tracking occluded or hidden objects using a Kalman Filter, and multiple objects tracking are covered. An example of tracking a moving ball will be used.
MATLAB
3
star
5

auvsi-cv-motionEstimation

Learn how we perceive motion and how to estimate motion using a technique called Optical Flow. You can use three algorithms to implement optical flow using the Computer Vision Toolbox. These three algorithms are Horn-Schunck method, Farneback method, and Lucas-Kanade method. An example of a robot boat moving through a field of buoys will be used.
MATLAB
2
star
6

CarND-Vehicle-Detection

Detect cars in a video frame using color, spatial and HoG feature extraction and a traditional machine learning classifier model such as SVM.
Jupyter Notebook
1
star
7

CarND-PID-Control

Use a PID control to drive a simulated car on its track. Perform parameter tuning using the Twiddle logic.
C++
1
star